Quantitative Imaging and Analysis Lab

Congratulations to  runner-up Hae Sol Moon of the Robert F. Wagner All-Conference Best Student Paper Award, sponsored by SPIE and the Medical Imaging Perception Society!   

In our study, we adopted an integrative approach that combined behavioral assessments, brain imaging, and blood transcriptomics to focus on the transition from middle to old age in APOE2 mice, leading to the identification of critical brain sub-networks and regions such as the cingulate cortex; we utilized Sparse Multiple Canonical Correlation Analysis (SMCCA) for modeling and graph neural network predictions, providing valuable insights into brain connectivity, aging, sex differences, and potential therapeutic targets.

Hae Sol Moon, Ali Mahzarnia, Jacques Stout, Robert J. Anderson, Madison Strain, Jessica T. Tremblay, Zay Yar Han, Andrei Niculescu, Anna MacFarlane, Jasmine King, Allison Ashley-Koch, Darin Clark, Michael W. Lutz & Alexandra Badea, Multivariate Investigation of Aging in Mouse Models with Alzheimer’s Protective APOE2 Allele: A Fusion of Cognitive Metrics, Brain Imaging, & Blood Transcriptomics, Brain Structure and Function, https://doi.org/10.1007/s00429-023-02731-x 

An exciting publication on our collaborative research focusing on the innovative applications of 3D Bioprinting and Photon-Counting CT.

Gil CJ, Evans CJ, Li L, Allphin AJ, Tomov ML, Jin L, Vargas M, Hwang B, Wang J, Putaturo V, Kabboul G, Alam AS, Nandwani RK, Wu Y, Sushmit A, Fulton T, Shen M, Kaiser JM, Ning L, Veneziano R, Willet N, Wang G, Drissi H, Weeks ER, Bauser-Heaton HD, Badea CT, Roeder RK, Serpooshan V. Leveraging 3d Bioprinting And Photon-Counting Computed Tomography to Enable Noninvasive Quantitative Tracking of Multifunctional Tissue Engineered Constructs. Adv Healthc Mater. 2023 Sep 14:e2302271. doi: 10.1002/adhm.202302271. PMID: 37709282.

Read the full paper here

A big thank you to our team and collaborators..

Nadkarni, R.; Clark, D.P.; Allphin, A.J.; Badea, C.T. A Deep Learning Approach for Rapid and Generalizable Denoising of Photon-Counting Micro-CT Images. Tomography 2023, 9, 1286-1302. https://doi.org/10.3390/tomography9040102

Our QIAL developed Multi-Channel CT Reconstruction (MCR) Toolkit addresses unique challenges associated with in vivo preclinical micro-CT and supporting the translation of these advancements to the clinical domain.

We have now published a paper in Medical Physics detailing our toolkit’s capabilities and functions:

Clark DP, Badea CT. MCR toolkit: A GPU-based toolkit for multi-channel reconstruction of preclinical and clinical x-ray CT data. Med. Phys.. 2023;1-22. https://doi.org/10.1002/mp.16532 

Our group contributed to these new papers from the co-clinical imaging research program (CIRP) :

1.Moore, S.M.; Quirk, J.D.; Lassiter, A.W.; Laforest, R.; Ayers, G.D.; Badea, C.T.; Fedorov, A.Y.; Kinahan, P.E.; Holbrook, M.; Larson, P.E.Z.; Sriram, R.; Chenevert, T.L.; Malyarenko, D.; Kurhanewicz, J.; Houghton, A.M.; Ross, B.D.; Pickup, S.; Gee, J.C.; Zhou, R.; Gammon, S.T.; Manning, H.C.; Roudi, R.; Daldrup-Link, H.E.; Lewis, M.T.; Rubin, D.L.; Yankeelov, T.E.; Shoghi, K.I. Co-Clinical Imaging Metadata Information (CIMI) for Cancer Research to Promote Open Science, Standardization, and Reproducibility in Preclinical Imaging. Tomography 2023, 9, 995-1009. https://doi.org/10.3390/tomography9030081

2.Gammon, S.T.; Cohen, A.S.; Lehnert, A.L.; Sullivan, D.C.; Malyarenko, D.; Manning, H.C.; Hormuth, D.A.; Daldrup-Link, H.E.; An, H.; Quirk, J.D.; Shoghi, K.; Pagel, M.D.; Kinahan, P.E.; Miyaoka, R.S.; Houghton, A.M.; Lewis, M.T.; Larson, P.; Sriram, R.; Blocker, S.J.; Pickup, S.; Badea, A.; Badea, C.T.; Yankeelov, T.E.; Chenevert, T.L. An Online Repository for Pre-Clinical Imaging Protocols (PIPs). Tomography 2023, 9, 750-758. https://doi.org/10.3390/tomography9020060